Publications
Kumar, S.*, Sumers, T. R.*, Yamakoshi, T., Goldstein, A., Hasson, U., Norman, K. A., Griffiths, T.L., Hawkins, R.D., Nastase, S. A. (2022). Reconstructing the cascade of language processing in the brain using the internal computations of a transformer-based language model. bioRxiv. (under review)
Kumar, S., Correa, C. G., Dasgupta, I., Marjieh, R., Hu, M. Y., Hawkins, R. D., Daw, N.D., Cohen, J.D., Narasimhan, K., & Griffiths, T. L. (2022). Using Natural Language and Program Abstractions to Instill Human Inductive Biases in Machines In Proceedings of the 36th Conference on Neural Information Processing Systems (NeurIPS) 2022. arXiv [Outstanding Paper Award, Top 13/10K+ submissions]
Kumar, S., Dasgupta, I., Marjieh, R., Daw, N. D., Cohen, J. D., & Griffiths, T. L. (2022). Disentangling Abstraction from Statistical Pattern Matching in Human and Machine Learning. arXiv (under review)
Kumar, S., Dasgupta, I., Cohen, J. D., Daw, N. D., & Griffiths, T. L. (2021). Meta-Learning of Structured Task Distributions in Humans and Machines. In Proceedings of the 9th International Conference on Learning Representations (ICLR) 2021. arXiv
Kumar, S., Ellis, C.T., O'Connell, T.P., Chun, M.M., Turk-Browne, N.B. (2020) Searching through functional space reveals distributed visual, auditory, and semantic coding in the human brain. PLoS Computational Biology, 16(12) e1008457.
Kumar, S., Yoo, K., Rosenberg, M. D., Scheinost, D., Constable, R. T., Zhang, S., ... & Chun, M. M. (2019). An information network flow approach for measuring functional connectivity and predicting behavior. Brain and behavior, 9(8), e01346.